Computation of Weight Function of 2qth Order Virtual Array to Analyse the Estimation Performance
ID:31 View Protection:ATTENDEE Updated Time:2020-08-05 10:16:59 Hits:492 Oral Presentation

Start Time:2020-06-09 15:00(Asia/Shanghai)

Duration:20min

Session:R Regular Session » R04Computational and Optimization Techniques for Multi-Channel Processing

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Abstract
To estimate the large number of sources using an array of lesser number of sensors is an important problem and of interest to many researchers. This problem has also been tackled with the virtual array based approach where the covariance and cumulant lags provide a virtual sensor. Here, an important parameter which affects the parameter estimation accuracy and latency is weight function. The weight function is defined as the frequency of occurrence of each virtual sensor in the virtual array. We provide the close-form expression of higher order virtual array corresponding to linear array. Afterwards, we have analytically evaluated the weight function of virtual array and study the effect of the weight function on parameter estimation. Simulation results show the parameter estimation accuracy is significantly improve with high weight function.
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Speaker
Payal Gupta
Indian Institute of Technology Delhi, India

Submission Author
Payal Gupta Indian Institute of Technology Delhi, India
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Important Date
  • Conference Date

    Jun 08

    2020

    to

    Jun 11

    2020

  • Jan 12 2020

    Draft paper submission deadline

  • Apr 15 2020

    Early Bird Registration

Sponsored By
IEEE Signal Processing Society
Organized By
Zhejiang University
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